DNA spectrograms express the periodicities of each of the four nucleotides A, T, C, and G in one or several genomic sequences to be analyzed. DNA spectral analysis can be applied to systematically investigate DNA patterns, which may correspond to relevant biological features. As opposed to looking at nucleotide sequences, spectrogram analysis may detect structural characteristics in very long sequences that are not identifiable by sequence alignment. Alignment of DNA spectrograms can be used to facilitate analysis of very long sequences or entire genomes at different resolutions. Standard clustering algorithms have been used in spectral analysis to find strong patterns in spectra. However, as they use a global distance metric, these algorithms can only detect strong patterns coexisting in several frequencies. In this paper, we propose a new method and several algorithms for aligning spectra suitable for efficient spectral analysis and allowing for the easy detection of strong patterns in both single frequencies and multiple frequencies.